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ML Systems Performance Engineer

Bengaluru, IND · Bengaluru, Karnataka, India

Actively hiring, first seen by us today
Pay
Pay not listed
Work setting
Hybrid — work setting source
Location type: Hybrid
From the employer’s posting
Employment
Full-time — employment source
Employment type: Full-time
From the employer’s posting
Team
Software Engineering › Inference Core — team source
Department: Software Engineering › Inference Core
From the employer’s posting

What you’ll work on

Full posting

Engineers on the inference performance team operate at the intersection of hardware and software, driving end-to-end model inference speed and throughput.

  • Build kernel-level and end-to-end performance models for ML models

  • Optimize kernel microcode and compiler algorithms for inference speed

  • Debug runtime performance across the system and cluster

  • Build tools to visualize performance data from the wafer and cluster

From the employer’s posting
Engineers on the inference performance team operate at the intersection of hardware and software, driving end-to-end model inference speed and throughput. Their work spans low-level kernel performance debugging and optimization, system-level performance analysis, performance modeling and estimation, and the development of tooling for performance projection and diagnostics.
Build performance models (kernel-level, end-to-end) to estimate the performance of state of the art and customer ML models.
Optimize and debug our kernel micro code and compiler algorithms to elevate ML model inference speed, throughput and compute utilization on the Cerebras WSE.
Debug and understand runtime performance on the system and cluster.
Develop tools and infrastructure to help visualize performance data collected from the Wafer Scale Engine and our compute cluster.

What you’ll bring

All qualifications

Core experience

  • Bachelor's, Master's or PhD in Electrical Engineering or Computer Science
  • 3+ years in computer architecture, CPU/GPU performance, kernel optimization or HPC
  • Strong background in computer architecture
  • Exposure to low-level deep learning and LLM math
  • Comfort with C++ and Python
Qualification wording
Bachelors / Masters / PhD in Electrical Engineering or Computer Science.
3+ years of experience in a relevant domain (Computer Architecture, CPU/GPU Performance, Kernel Optimization, HPC).
Strong background in computer architecture.
Exposure to and understanding of low-level deep learning / LLM math.
Comfort with C++ and Python.
Education & alternatives
Requirements - Bachelors / Masters / PhD in Electrical Engineering or Computer Science. - Strong background in computer architecture.
Apply at Cerebras Systems

Posting record

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Actively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Nov 8, 2026today
Recorded sightings
1
Employer says posted
Jun 16, 2026

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How this job compares

Time since we first saw it

Day 0

Early. Similar jobs usually come down between day 7 and day 72.

From 4,655 similar postings that came down. Coming down is not always a hire.

Cerebras Systems is hiring

13 open jobs

Open jobs by the week we first saw them, last 12 weeks.

Hiring record

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  • C++
  • Python
Where the posting names them
- Exposure to performance profiling and debug on any system pipeline. - Comfort with C++ and Python. Why Join Cerebras

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Has Cerebras Systems posted this job before?

Yes. We’ve followed one other ML Systems Performance Engineer job there since November 2026. It is still up.

  1. United States AndStill up after 1 day, first seen Nov 8
  2. This jobUp 1 day so far, first seen Nov 8

Demand for ML Engineer roles

New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.

Weekly new ML Engineer postings at the same employers, from the week of August 17 to the week of October 26. The fewest in a week was 619, the most 1,091, and the latest week had 863.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 5 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under ML Engineer, by the work the posting describes.

ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.

Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.

A data scientist often works out which model to build; an ML engineer makes it run reliably in production.

US government figures for computer and information research scientists

Median yearly pay, May 2025
$140,300
Expected change, 2025 to 2035
21.8% more jobsagainst 3.5% for all jobs

The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.

Job description

View original posting ↗

Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.

This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.

Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.

About The Role

Engineers on the inference performance team operate at the intersection of hardware and software, driving end-to-end model inference speed and throughput. Their work spans low-level kernel performance debugging and optimization, system-level performance analysis, performance modeling and estimation, and the development of tooling for performance projection and diagnostics.

Responsibilities

  • Build performance models (kernel-level, end-to-end) to estimate the performance of state of the art and customer ML models.

  • Optimize and debug our kernel micro code and compiler algorithms to elevate ML model inference speed, throughput and compute utilization on the Cerebras WSE.

  • Debug and understand runtime performance on the system and cluster.

  • Develop tools and infrastructure to help visualize performance data collected from the Wafer Scale Engine and our compute cluster.

Requirements

  • Bachelors / Masters / PhD in Electrical Engineering or Computer Science.

  • Strong background in computer architecture.

  • Exposure to and understanding of low-level deep learning / LLM math.

  • Strong analytical and problem-solving mindset.

  • 3+ years of experience in a relevant domain (Computer Architecture, CPU/GPU Performance, Kernel Optimization, HPC).

  • Experience working on CPU/GPU simulators.

  • Exposure to performance profiling and debug on any system pipeline.

  • Comfort with C++ and Python.

Why Join Cerebras

People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:

  1. Build a breakthrough AI platform beyond the constraints of the GPU.

  2. Publish and open source their cutting-edge AI research.

  3. Work on one of the fastest AI supercomputers in the world.

  4. Enjoy job stability with startup vitality.

  5. Our simple, non-corporate work culture that respects individual beliefs.

Find out more about what it's like to work at Cerebras here!

Apply today and become part of the forefront of groundbreaking advancements in AI!

Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.

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Bengaluru, Karnataka, India

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